class_docstr: Pose feature extractor.
  
  Extracts pose features based on estimated body landmark keypoints.
code: def __init__(self, *args, **kwargs) -> None:
      super().__init__(*args, **kwargs)
  
      weights = KeypointRCNN_ResNet50_FPN_Weights.DEFAULT
      model = keypointrcnn_resnet50_fpn(weights=weights)
      self.model = model
      self.transform = model.transform
      self.backbone = model.backbone
      self.roi_heads = model.roi_heads
  
imports: from __future__ import annotations
  from enum import Enum
  import torch
  from torch import Tensor, nn
  from torchvision.models.detection import KeypointRCNN_ResNet50_FPN_Weights, keypointrcnn_resnet50_fpn
  from torchvision.models.detection.roi_heads import keypointrcnn_inference
  from torchvision.ops import roi_align
  from torchvision.transforms import Normalize
  from anomalib.models.ai_vad.clip import clip
label_desc: Use image node_id 1 to create a new PoseExtractor object from inherited base classes: nn with example: obj = PoseExtractor()